Single Origin is the AI guardrail for enterprise data.

We build the "Trust Layer" that allows enterprises to safely adopt Agentic AI. By integrating directly into your Code Review and IDE workflows, Single Origin acts as an automated gatekeeper that prevents AI hallucinations, enforces business logic, and optimizes query performance before code ever reaches production.

The Short Version: GitHub Copilot helps you write code faster. Single Origin ensures that code is actually correct and safe for your specific data infrastructure.

Why Single Origin?

The "Garbage-In, Garbage-Out" Crisis

Enterprises are racing to adopt AI Agents to automate data engineering. However, while LLMs can generate SQL 100x faster than humans, they lack "Enterprise Context."

• Generic LLMs Guess: They don’t know your legacy schema, your deprecated columns, or your compliance boundaries.
• The Velocity Trap: Without a guardrail, AI agents generate technically valid SQL that is architecturally disastrous—hallucinating metrics and ignoring business logic.
• The Human Bottleneck: Senior engineers are forced to spend 50% of their time acting as "human error-checkers" for AI-generated code.

Single Origin solves this by shifting governance left. We don't wait for a bad query to break a dashboard or burn your budget. We block it in the Pull Request.

Core Concepts

1. Context Engineering (The Brain)

Generic AI models are trained on public internet data. Single Origin is trained on your production history. We ingest your query logs, metadata, and lineage to build a deep understanding of intent.

• Semantic Awareness: We know that user_id in Table A must join with account_id in Table B.
• Lineage Intelligence: We understand how data flows through your specific pipelines, allowing us to predict downstream impact.

2. The Semantic Guardrail (The Shield)

We provide a "Semantic Firewall" that sits between your AI Agents (or junior engineers) and your data warehouse.

• Anti-Hallucination: If an Agent invents a metric or joins unrelated tables, we flag it immediately.
• Business Logic Enforcement: We ensure queries adhere to your defined architectural standards.

3. Automated Refactoring (The Optimizer)

We use your production context to proactively optimize infrastructure.

• Deduplication: We identify redundant queries and merge them.
• Materialized View Recommendations: We automatically suggest views to offload heavy compute patterns.
• Index Tuning: We recommend high-performance indexes based on actual access patterns.

How It Works

Single Origin integrates seamlessly into your existing engineering workflow:

1. Connect: Link Single Origin to your Data Warehouse (Snowflake, BigQuery, Databricks) and Version Control System (GitHub, GitLab).
2. Analyze: We scan your query history to build a custom "Enterprise Context" model.
3. Gatekeep:
   1. In the IDE: Engineers get real-time feedback as they type.
   2. In the PR: We automatically review code changes, commenting on risks, costs, and logic errors.
4. Optimize: We continuously monitor production to suggest architectural improvements.

Comparision With Generic AI

Trusted By

We are the standard for data-forward teams who refuse to compromise on accuracy.

• Coinbase: Uses Single Origin as a semantic firewall to ensure financial data compliance.
• Roblox: Reduced metric storage by 15% and eliminated billions of unneeded time series.
• Palo Alto Networks: Secures their data foundation for rapid AI adoption.

Our Team

We worked as senior data infrastructure leaders from Uber, Snap, Stripe, and Meta, and now we are redefining how modern data teams work.